Automatic content analysis method and system

ABSTRACT

A method of analyzing images over time is provided herein. The method includes: capturing a plurality of images each associated with specified objects in specified locations such that a specified area is covered; specifying regions of interest (ROI) in each of the captured images; repeating the capturing with at least one of: a different location, a different orientation, and a different timing such that the captured images are associated with the specified covered area; and comparing the captured imaged produced in the capturing with the captured imaged produced in the repeating of the capturing to yield comparison between the captured objects by comparing specified ROI.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is the U.S. national phase of PCT applicationPCT/IB2010/054538, filed 7 Oct. 2010, published 14 Apr. 2011 as WO2011/042876, and claiming priority to U.S. Provisional PatentApplications No. 61/249,263 filed Oct. 7, 2009; 61/286,403 filed Dec.15, 2009; 61/329,109 filed Apr. 29, 2010; 61/330,997 filed May 4, 2010;61/333,809 filed May 12, 2010; and 61/347,468 filed May 24, 2010.

BACKGROUND

1. Technical Field

The present invention relates to image and video processing and moreparticularly, to such processing based on time-based changes.

2. Discussion of the Related Art

Using images of scenes taken on different time slots is a well-knownmethod to detect, classify, and analyze changes to the scene or specificobjects contained therein. Changes analysis may have furtherapplications that may vary, according to the scope of the time-spacethat is being monitored.

The introduction of ubiquitous cellular communication devices equippedwith imaging capabilities, some with positioning means, poses achallenge for a system and method for controlling these devices in anefficient manner for configuring them for object analysis that ischanges based on one hand and has a wide span of applications, on theother hand.

BRIEF SUMMARY

One aspect of the invention provides a method of analyzing images overtime. The method includes: capturing a plurality of images eachassociated with specified objects in specified locations such that aspecified area is covered; specifying regions of interest (ROI) in eachof the captured images; repeating the capturing with at least one of: adifferent location, a different orientation, and a different timing suchthat the captured images are associated with the specified covered area;and comparing the captured imaged produced in the capturing with thecaptured imaged produced in the repeating of the capturing to yieldcomparison between the captured objects by comparing specified ROI.

Other aspects of the invention may include a system arranged to executethe aforementioned methods and a computer readable program configured toexecute the aforementioned methods. These, additional, and/or otheraspects and/or advantages of the embodiments of the present inventionare set forth in the detailed description which follows; possiblyinferable from the detailed description; and/or learnable by practice ofthe embodiments of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of embodiments of the invention and to showhow the same may be carried into effect, reference will now be made,purely by way of example, to the accompanying drawings in which likenumerals designate corresponding elements or sections throughout.

In the accompanying drawings:

FIG. 1 is a flowchart of acts performed in accordance with an exemplaryembodiment of the invention;

FIG. 2 is a scheme describing the system and process in accordance withan exemplary embodiment of the invention;

FIG. 3 is a high level block diagram illustrating a data processing andpresenting according to some embodiments of the invention;

FIG. 4A is a scheme describing a system and process in accordance withan exemplary embodiment of the invention;

FIG. 4B is a side view of a system and process in accordance with anexemplary embodiment of the invention described in 4A;

FIG. 5 is a flowchart of acts performed in accordance with an exemplaryembodiment of the invention;

FIG. 6 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention;

FIG. 7 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention;

FIG. 8 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention;

FIG. 9 is a scheme describing a system and process m accordance with anexemplary embodiment of the invention;

FIG. 10 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention;

FIG. 11 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention;

FIG. 12 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention;

FIG. 13 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention; and

FIGS. 14A and 14B are a scheme describing a system and process inaccordance with an exemplary embodiment of the invention.

FIG. 15 is a schematic illustration of an information display system

The drawings together with the following detailed description makeapparent to those skilled in the art how the invention may be embodiedin practice.

DETAILED DESCRIPTION

With specific reference now to the drawings in detail, it is stressedthat the particulars shown are by way of example and for purposes ofillustrative discussion of the preferred embodiments of the presentinvention only, and are presented in the cause of providing what isbelieved to be the most useful and readily understood description of theprinciples and conceptual aspects of the invention. In this regard, noattempt is made to show structural details of the invention in moredetail than is necessary for a fundamental understanding of theinvention, the description taken with the drawings making apparent tothose skilled in the art how the several forms of the invention may beembodied in practice.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not limited in its applicationto the details of construction and the arrangement of the components setforth in the following description or illustrated in the drawings. Theinvention is applicable to other embodiments or of being practiced orcarried out in various ways. Also, it is to be understood that thephraseology and terminology employed herein is for the purpose ofdescription and should not be regarded as limiting.

To facilitate understanding the present invention, the followingglossary of terms is provided. It is to be noted that terms used in thespecification but not included in this glossary are considered asdefined according the normal usage of the computer science art, oralternatively according to normal dictionary usage.

The term “DB” as used herein in this application, is defined as database

The term “GIS” as used herein in this application, is defined as acomputer system designed to allow users to collect and/or manage and/oranalyze spatially referenced information.

The term “surface objects” as used herein in this application, isdefined as objects that are on the surface of a planet such asbuildings, roads, canals, fields.

The term “surface data” as used herein in this application is defined asinformation gathered on surface objects such as aerial images, satelliteimages, ground images, and images taken with a handheld camera orcamera-phone, GIS information, LIDAR data, Radar scans.

The term “image” as used herein in this application is defined as visualrepresentation that can be presented on two dimensional or threedimensional surfaces. Images can be taken in any part of theelectromagnetic spectrum such as visible light, infrared, ultraviolet,X-rays, Terahertz, Microwaves, and Radio frequency waves. An Image couldbe taken from one or more sensors or with one sensors with multiplelenses in order to create a 3 dimensional image.

The term “photo” as used herein in this application is defined as imagein the visible light.

The term “DSM” as used herein in this application, is defined as atopographic elevation model of the Earth surface that provides ageometrically representation for the purpose of overlaying the modelwith a wide range of GIS data. DSM provides a surface elevation of everynatural and artificial feature visible within the image area.

The term “DEM” as used herein in this application, is defined as adigital representation of a continuous variable over a two-dimensionalsurface by a regular array of z values referenced to a common datum.

The term “DTM” as used herein in this application, is defined as DigitalTerrain Model is a 3D representation of the Earth's surface. Itsconstruction includes a height model (DEM) and overlaid with map datarelating to features on the surface (Map Data or Aerial Photograph).

The term “INS” as used herein in this application, is defined as anavigation aid that uses a computer, motion sensors (accelerometers) androtation sensors (gyroscopes) to continuously calculate via deadreckoning the position, orientation, and velocity (direction and speedof movement) of a moving object without the need for externalreferences.

The term “GPS” as used herein in this application, is defined as Asystem based on satellites that allows a user with a receiver todetermine precise coordinates for their location on the earth's surface.

The term “Micronavigation” as used herein in this application, isdefined as a method based on visual objects that allows a user todetermine precise coordinates for their location on the earth's surfacein a precision that is higher than of a GPS system.

The term “Real Time Map” as used herein in this application, is definedMap having layer that are updated in a latency that is lower than thelatency needed to benefit from the map considering the changes in thelayer. For example a real time traffic jam map is a map that is updatedfor at least the last hour as that jams might be gone in an hour

The term “GPU” as used herein in this application, is defined as anapparatus adapted to reduce the time it takes to produce images on thecomputer screen by incorporating its own processor and memory, havingmore than 16 CPU cores, such as GeForce 8800.

The term “Keypoint” as used herein in this application, is defined asinterest points in an object. For example, in the SIFT framework, theimage is convolved with Gaussian filters at different scales, and thenthe difference of successive Gaussian-blurred images are taken.Keypoints are then taken as maxima/minima of the Difference ofGaussians. Such keypoint can be calculated for the original image or fora transformation of the original image such as an affine transform ofthe original images.

The term “Keypoint descriptor” as used herein in this application, isdefined as a descriptor of a key point. For example, in the SIFTframework the feature descriptor is computed as a set of orientationhistograms on neighborhoods. The orientation histograms are relative tothe keypoint orientation and the orientation data comes from theGaussian image closest in scale to the keypoint's scale. Just likebefore, the contribution of each pixel is weighted by the gradientmagnitude, and by a Gaussian with a 1.5 times the scale of the keypoint.Histograms contain 8 bins each, and each descriptor contains an array of4 histograms around the keypoint. This leads to a SIFT feature vectorwith (4×4×8=128 elements).

The term “Visual content item” as used herein in this application, isdefined as an object with visual characteristics such as An image filelike BMP, JPG, JPEG, GIF, TIFF, PNG files; a screenshot; A video filelike AVI, MPG, MPEG, MOV, WMV, FLV files or a one or more frame of avideo.

The term LIDAR as used herein in this application is defined as is anoptical remote sensing technology that measures properties of scatteredlight to find range and/or other information of a distant target. Theprevalent method to determine distance to an object or surface is to uselaser pulses

The term “Visual object” as used herein in this application, is definedas a content that includes visual information such as Visual contentitem, images, photos, videos, IR image, magnified image, an imagesequence or TV broadcast.

The term “Camera” as used herein in this application is defined as meansof capturing a visual object

The term Terminal as used herein in this application, is defined as anapparatus adapted to show visual content such as a computer, a laptopcomputer, Mobile phone or a TV.

The term Visual similarity as used herein in this application, isdefined as the measure of resemblances between two visual objects thatcan be comprised of:

-   -   The fit between their color distributions such as the        correlation between their HSV color histograms;    -   The fit between their texture;    -   The fit between their shapes;    -   The correlation between their edge histograms;    -   Face similarity;    -   methods that include local descriptors and/or keypoints such as        SIFT see (en.wikipedia.org/wiki/Scale-invariant feature        transform), ASIFT, SURF and MSR.

The term “Visual analysis” as used herein in this application, isdefined as the analysis of the characteristics of visual objects such,as visual similarity, coherence, hierarchical organization, concept loador density, feature extraction and noise removal

The term “Sound analysis” as used herein in this application, is definedas the analysis of audio waves such as speech recognition, songrecognition, and sentiment recognition

The term “Text similarity” as used herein in this application, isdefined as Measure the pair-wise similarity of strings. Text similaritycan score the overlaps found between two strings based on text matching.Identical strings will have a score of 100% while “car” and “dogs” willhave close to zero score. “Nike Air max blue” and Nike Air max red” willhave a score which is between the two. Further string similarity metricsare described in http://en.wikipedia.org/wiki/String metric.

The term “Regular expression” as used herein in this application, isdefined as a string that provides a concise and flexible means foridentifying strings of text of interest, such as particular characters,words, or patterns of characters. Seehttp://en.wikipedia.org/wiki!Regular_expression.

The term “Text analysis” as used herein in this application, is definedas the analysis of the structural characteristics of text, as textsimilarity, coherence, hierarchical organization, concept load ordensity. (Seegoogle.com/search?h1=en&safe=off&r1z=1CICHMG_eniL291L303&q=define:text+analysis&btnG=Search).Text analysis can use regular expressions.

The term “LPR” as used herein in this application, is defined as:license plate recognition as described inen.wikipedia.org/wiki/Automatic_number_plate_recognition.

The term “OCR” as used herein in this application, is defined as Theelectronic identification and digital encoding of printed or handwrittencharacters by means of an optical scanner and specialized software

The term “Symbol analysis” as used herein in this application, isdefined as analysis of symbolic data such as: OCR, LPR, hand writerecognition, bar-code recognition, and QR code recognition.

The term “Capturing data” as used herein in this application, is definedas data taken while capturing a visual object such as: X-Y-Zcoordinates; 3 angles; Manufacturer; Model; Orientation (rotation)top-left; Software; Date and Time; YCbCr Positioning centered;Compression; x-Resolution; y-Resolution; Resolution Unit; Exposure Time;FNumber; Exposure Program; Exif Version; Date and Time (original); Dateand Time (digitized); Components Configuration Y Cb Cr -; CompressedBits per Pixel; Exposure Bias; Max Aperture Value; Metering ModePattern; Flash fired or not; Focal Length; Maker Note; Flash PixVersion; Color Space; Pixel X Dimension; Pixel Y Dimension; File Source;Interoperability Index; Interoperability Version; derivatives of theabove such as acceleration in the X-axis; The term “Capturing dataanalysis” as used herein in this application, is defined as the analysisof Capturing data.

The term “Service location” as used herein in this application, isdefined as a physical place where objects can be serviced and/or fixedsuch as a mobile carrier service center.

The term “Location based analysis” as used herein in this application,is defined as analysis of local data such as GPS location, triangulationdata, RFID data, and street address. Location data can for exampleidentify the service location or even the specific part of the servicelocation in which the visual object was captured.

The term “Content analysis” as used herein in this application, isdefined as the combination of text analysis, visual analysis, symbolanalysis, location based analysis, Capturing data analysis, soundanalysis and/or analysis of other data such as numerical fields (pricerange), date fields, logical fields (Female/male), arrays andstructures, and analysis history.

The term “Content Match” as used herein in this application, is definedas a numerical value that describes the results of the content analysisthat computes the similarity between one or more visual objects, or alogical value that is true in case said similarity is above a certainthreshold.

The term “Data Clustering methods” as used herein in this application,is defined as the assignment of objects into groups (called clusters) sothat objects from the same cluster are more similar to each other thanobjects from different clusters. Often similarity is assessed accordingto a distance measure. See en.wikipedia.org/wiki/Data_clustering

The term “Driver warning” as used herein in this application, is definedas a warning comprising: Audio alert such as a beep sound; A Visualalert such as a red light and/or a text such as: “stop”, “slow down”,“approaching destination”, “pedestrian are crossing”, “crossing border”;A Tactile feedback such as vibrations;

The term “Driving intervention” as used herein in this application, isdefined as automatic driving operation such as: Braking; Slowing down;Complete stop; Taking a right turn; Taking a left turn; Turning lightson; Tightening the seat belt;

The term “Server reaction” as used herein in this application, isdefined as an action performed on a remote server such as sending amessage such as an SMS to a specific person or sending a team to aspecific location.

The term “System reaction” as used herein in this application, isdefined as a driver warning, a driving intervention or server reactioncombination of them.

FIG. 1 is a flowchart of acts performed in accordance with an exemplaryembodiment of the invention; and

System 100 performs the following steps:

Surface data is captured 200 in manner further described in FIG. 2.Optionally, the Surface data is compared 300 to surface data taken orcreated at an earlier time. And the difference results are presented 350as further described in FIG. 3.

In case changes are detected further actions 400 can be taken such asOrdering system 222 such as plane to capture another image of thechanged object such as:

1. Taking

-   -   Enlarged image Closer    -   image Oblique(diagonal)    -   An image of different modality than the original one such as IR        image in case a visible range image was originally taken    -   Same image to verify the change

2. Monitor system 200 by reporting an abnormal number of changes.

3. Performing an onsite manned or unmanned inspection of the object fromthe ground to further check/verify reported changes

This will be more beneficial in case comparison is taken in “real time”such as time short enough to perform action 400 in the same session suchas the same flight session.

FIG. 2 is a scheme describing the system and process in accordance withan exemplary embodiment of the invention. System 200 performs theprocess of gathering surface data using:

1) A. devices such as:

a) A camera system 212 comprising a camera 216 and optionally a GPS

214 and/or INS units 215. It is to be noted that preferably there aresimilar systems such as 213 capturing data at the same time. In asimilar manner there could be further similar system such 218 and/or 219gathering data at the same time and/or being at the same location and/orgathering data of the same surface object.

b) A LIDAR 218 or RADAR system using pulses of waves to capture data.

c) A mobile camera phone 219, preferably one that resides in an ordinarymobile phone or a navigation system, and preferably one that is able toprovide further geo-location data such as GPS or other triangulationdata.

2) Airborne Platform to carry said devices such as:

-   -   a) An airplane 222 b) An airship 226    -   c) A satellite 224

3) A surface level platform such as:

-   -   a) A vehicle such as car 110 or a motorcycle in which case 219        can be a navigation system placed on the inner part of a car        windows and having a camera and preferably captures visual        object while moving. Optionally car 110 carries a camera such as        122 close to it front or back license plate. Alternatively,        camera 122 is installed on the front and/or back license plate        of the car.    -   b) A building 234 c) A person 236    -   d) A human body part such as ear 237 having an earpiece 238        equipped with camera 122

FIG. 3 is a high level block diagram illustrating a data processing andpresenting according to some embodiments of the invention.

The inputs for system 250 are comprised of:

260: DEM and/or DSM and/or DTM collected using systems such as 200

252: Surface data

254: images, and preferably models that include images and X-Y-Z/Polarcoordinates for each pixel/object in said image

256: LIDAR or Radar data

258: GPS and/or INS data such as 6 dimensional data comprised oflatitude, longitude, height, pitch, roll, and yaw.

264 Visual object

266 Capturing data

268 Location data

270 Symbolic data

272 Textual data

274 Historical data, such as the last object identified at the samecoordinates.

276 sound waves

Said inputs and historical data of the same location and/or object areprocessed by subsystem 300. Subsystem 300 is preferable using one ormore GPU's 310 as processing of large data sets requires a significantamount of computation and the usage of parallel algorithms such askeypoint descriptors comparison.

System 300 is further comprised of two subsystems:

Subsystem 320 that does content analysis such change detection betweentwo or more data sets such as:

322 keypoint based comparison methods such as SIFT Using methods such asScale-invariant feature transform or similar methods such as GLOH(Gradient Location and Orientation Histogram), PCA-SIFT and MSR. Suchmethod usually use keypoint localization step, an later on compare manykeypoint descriptors in one object to a plurality of keypointdescriptors in another object and hence require quick computation inorder to compare an object to a plurality of object within a responsetime an ordinary user would expect. The higher the number or thepercentage of keypoint descriptors in a first object than match (exactlyor approximately) keypoint descriptors in a second object the higher isthe similarity between the two objects. Preferably the module usesKeypoints of transformed object based methods. Such transformation caneven further use 250 data such as 258 and/or 260 to create estimatedneeded compensation transform such is there is a 5° deviation betweentwo images of the same building it can correct the resulting keypointaccordingly. Using methods such as Haar wavelet transform. Comparing thecolor histograms of the object to other color histograms. The methodscan be used separately, one after another or in parallel. In case aheavily computational method such as (a) is used it is advisable to usea GPU such as 310 to attain a reasonable response time and to runparallel algorithms.

324 correlation based methods such as 2D correlation

Subsystem 340 used to filter in the more important changes comprising:

342 Object subtraction module, used to ignore object such as trees, andwater and grass.

344 a module to ignore mobile object such as cars or people using (theircalculated speed, size, or the fact they do not reappear in twoconsecutive images or two image modalities)

346 a module to focus on object of interest such as houses using theirvisual characteristics (such as shape, color, texture, known patterns,edges)

Subsystem 350 presents the data in a format useful for the intendedapplications such as:

352: Photo with marked changes from previous photo and preferablydigital signature in order to be legally accepted as evidence.

354: GIS output.

356: A report of unauthorized improvements done to objects such asadding a room to a house.

358: agricultural data such growth rate of crops

360: 3D views such as Urban maps

Reports as shown in 1240 and 1260

FIG. 4A is a front view of a system and process in accordance with anexemplary embodiment of the invention.

System 490 is located on the inner part of a vehicle such as 110. It canbe mounted on the front window 442 or the back window 444 of thevehicle. The system is comprised of:

Car mount 450 further comprising of:

Suction cup 456—a device, usually made of rubber or plastic, that sticksto smooth, nonporous surfaces such as 442. This device can be replacedby an adhesive unit.

Arm 454 attached to both 456 and 452. Sometimes arm 454 is flexible.

A cradle 452 that can grip a device such 120. Cradle is adapted toenable repeated quick and repeatable mounting and un-mounting(forexample in less than 5 seconds), for example by using side holders 453that grab device 120 from its left and right side. In some cases one ofthe corners of cradle 452 is eliminated or cut to clear line of sightfor camera 122 and/or 128.

Device 120 is a device having a processing unit, such as a smart-phonesuch as an iPhone device. Sometimes device 120 is mobile and sometimesit is stationary. Sometimes device 120 has multiple cores (such as agraphic card) that enable executing parallel algorithms. Sometimesdevice 120 has an internal and/or external antenna such as 121. Antenna121 can wirelessly connect the device to a public network such theInternet and thus transmit the information gathered by device to aremote server and/or to other users such as other users of a device suchas 120 and thereby share that information.

Device 120 can have one back side camera such as 122 or additionalcamera such as 128. Sometimes device 120 runs a second application suchas a Navigation application in parallel to performing the process ofFIG. 5. Sometimes though, camera is actively capturing images, device120 is adapted not to display the captured image.

Sometimes Device 120 uses means for receiving power such as cable 462that connects to the a car lighter socket such as 464.

Device 410 is a media player such as car radio.

FIG. 4B is a side view of a system and process in accordance with anexemplary embodiment of the invention described in 4A

The vehicle's driving direction is defined in 430.

The vehicle has a front window 442, a back window 444, and a roof 446.

The vehicle is driven by driver 140, drivers eye is marked 142.

Sometimes device 120 has additional sensors 124,126, these sensors canbe:

-   -   Microphone    -   Accelerometer    -   Compass    -   GPS or AGPS receiver    -   Magnetic sensors    -   Proximity sensor    -   Capacitive sensors    -   Finger print sensor    -   Chemical sensor    -   Machine olfaction sensor    -   CO2 sensor    -   Bio-sensors    -   A sensor matrix of any of the above    -   Temperature sensor either one that requires contact with the        measured medium or one capable of remote measurement of        temperature

For example a microphone can be used to capture sound waves indicating acar problem.

In Another example motion sensor 124 and/or camera 128 can be used as acar theft alarm, hence in case the car is moved while its owners are outof the car, it will produce an alarm sound and/or call and/or SMS itsowner and or the police.

A front camera such as 128 can capture a visual object, and its analysiscan indicate driver 140 has fallen asleep as his eye leads have beenclosed for a period longer than a predefined threshold.

Device 120 can also receive data from a remote server indicating such astriangulation data indicative of its location and/or estimated speed.

Camera 122 can be used to estimate the distanced 472 between 120 andanother object such as 130 of FIG. 6. Distance d can be estimated usingthe formula:d=S*WmaxI(2W*tan(a/2)

-   -   where:    -   474 a=the angular extent of a given scene that is imaged by        camera 122.    -   S=the known width of object such as object 130 in metric units    -   476 W=the width of object such as object 130 in pixel units    -   Wmax=the maximal width of an object in pixel units in camera 122

FIG. 5 is a flowchart of acts performed in accordance with an exemplaryembodiment of the invention.

The acts serve the content matching needed in the embodiments describedin figures such as 4, 6, 7, 8, 9, 10, 11

One of the inputs for the process is a visual object such as a photoframe captured by camera 122. Others are for example sensors 124,126input and other data as shown in 250 Processing can be performed ondevice 120 or on a remotes servers.

The following acts are performed, not necessarily in the below order:

509—Receive location data such as GPS, AGPS, Cellular triangulation dataand/or sensor 124,126 data such as acceleration, and camera 122,128 dataand time.

511—Use the above data to compute the speed in which 110 is traveling(both magnitude and direction in 3 axes. For example, two GPS points andin two time points give the average velocity. Speed can also becalculated using the camera data. Angular data from sensors data cangive the estimated horizon point. The horizon can be calculated usingthe camera data as well. Other possible computations are:

-   -   Tilt—both to the side (around Z axis) and to the front (around Y        axis), calculated from the orientation sensor values.    -   Horizon Line—calculated from the tilt of the device around its Y        axis and translated to pixel Y-coordinate according to the        screen resolution.    -   Bearing line—though it can be calibrated manually by the user        dragging the vertical bearing line. A few automatic methods are        possible:        -   Calculating the angle between the compass azimuth and the            GPS-based bearing azimuth        -   Calculating the angle between the phone screen and the car's            windshield based on the average forces working on the phone            (from the accelerometer sensor)        -   Calculating the driving direction using pattern recognition            of the street lane lines

512—An object is detected, for example a car such as 130.

514—The object is classified to a category, for example a car, amotorcycle or a person.

516—A specific object is identified, such as the car from previousframe, or a person called John Smith.

518—Specific object attributes are extracted such as:

-   -   Car color    -   Texture    -   Shape    -   License plate numbers    -   Hair color    -   Object dimension such car's width, persons height.

520—object can be counted such as counting the number of cars on theroad, or the number of shoppers 834 near store 832

522—distance and or direction is calculated to the object such as:

-   -   The distance from 122 as shown if FIG. 4B    -   the direction to the object such as the angular direction    -   The relative speed from the object.    -   The time to collision with the object

524—The risk of collision is calculated taking in account:

-   -   The device 120's speed using parameters such as GPS and devices        sensors such as 124.    -   Estimated time to collision    -   Road conditions    -   Car condition    -   Visibility    -   Drivers conditions such as estimated reaction time    -   Sensor information from 124,126

Device 120 or devices connected to it can than show to user such asdriver

140 and/or other users in vehicle 110 information such as:

526: object information such as any of the attributes described in 518

528: warning such as driver warning or advice such a suggestion tochange a lane using GIS info such as 1240 such as traffic flowinformation.

530: advertisements such as sales in store 834. Sometimes ads are localads of businesses close to 120.

The advertisements are optionally directed at inducing, promoting and/orencouraging purchase of products and/or services and/or acceptance ofideas. Optionally, the user to which the advertisements are displayed isnot charged for display of the advertisements, but rather the providerof the advertisements is charged for their display. In some cases theadvertisement is an audio sound such as a radio advertisement. Sometimesthe advertisements are displayed only when device 120 indicates the car110 is slow, in complete stop or in a traffic jam

Steps 512, 514, 516, 518 can all use Content analysis and content match.

Some of the steps 512-530 are optional.

FIG. 6 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention.

Scheme shows a first, lead vehicle 130 traveling along a road 620 andfollowed by a second vehicle 110 having device 120.

Driver 140 is driving the second vehicle 110. System 490 processesimages of the environment in front of the second vehicle 110 andproduces information out of them.

Using this information system 490 calculates distance (d) 472 betweentwo vehicles 110,130 and speed of second vehicle 110 at any given timeas further described in FIG. 5.

According to these parameters system 490 then processes images taken bycamera 122 and estimates the risk of collision between the two vehiclesfor example by comparing the estimated time to collision and the time tocollision threshold. The risk to collision can take in account thebreaking time, the cars relative distance, velocity, acceleration andjolt. Road conditions such as wet road (such as 826), oil spills, andthe presence of other car, and drivers 140 expected reaction time due tohis fatigue and his reaction time history.

If such an estimated risk crosses a predefined threshold and/or vehicle110 speed exceeds permissible, system reaction will occur.

Optionally, system 490 can extract further attributes of vehicle 130.such as a for sale sign 610, vehicle 130's car model, color, size,condition

If such a vehicle is identified, system 490 produces a relevant noticesuch as an alert for potential vehicles for sale within range.

These alerts are also accessible to all system's 490 users via web.

Optionally, system 490 creates a system reaction in case the distancebetween 110 and 130 and/or the estimated time to collision is below acertain threshold.

Alternatively, 130 is behind car 110 and system 490 creates a systemreaction in case the distance between 110 and 130 and/or the estimatedtime to collision is below a certain threshold. The system reaction canbe displayed on the back side such as through the back window 444 of 110using a back window sign.

FIG. 7 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention.

Person 140 drives his vehicle 110 having device 120. He is supposed todrive in accordance with lane markings 600.

Nevertheless, during driving, person 140 is falling asleep or not payingattention.

Consequently, vehicle driving direction 720 deviates beyond a certainthreshold from the middle of the lane markings 730

And even crosses the left marking.

System 490 process images taken by camera 122 and recognizes using stepssuch as the ones described in FIG. 5, the deviation from the middle ofthe lane. If such a deviation crosses a predefined threshold system 490reaction will occur.

Optionally, system 490 will use the input from camera 122 and/ormicrophone 124 to check whether the driver has used the left turnblinker 710 in which case no alert will be created.

FIG. 8 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention.

Scheme shows a vehicle/taxi 110 traveling along a road 620.

System 490 processes images taken by camera 122,128 of the environmentin front of the taxi 110 having device 120, and produces information anddata regarding items within driving range, such as:

-   -   People waiting for a taxi 812 optionally in a real time map    -   Pavement stone 818    -   Shops and businesses 834 and their relevant traction    -   Road conditions such as bump 822 or wet road 826    -   Traffic signs above the road level such as stop sign 816, or on        the road level such as zebra crossing 824    -   Landscape conditions such as blossoming field 814    -   Crowd 832, and his emotions, using features such as smile        recognition or by analyzing the sound of the crowd    -   Police cars, police man, traps, laser gun    -   Traffic lights color    -   Traffic jams    -   Low visibility    -   Traffic offenders and license plate recognition    -   Measure street cleanness level, Report is sent to        municipalities.    -   Water leaks, report is sent.

System 490 uses OCR technology to read and interpret traffic signs abovethe road level, this is Relevant to driving abroad. For example, Driver140 is driving in a foreign country. Traffic and

Information signs are written in a foreign language which he doesn'tunderstand. System 490 will recognize signs above road level, translateand alert driver 140 regarding relevant information.

Another example is, taxi driving along a road. System 490 recognizespeople at the side of the road raising their hand for a taxi, System 490then produces relevant notice, available to all system's users via web.

Yet, Another example is a car is driving along a road, a person face iscaptured and is compared against a person DB, for example:

Celebrity Faces DB in which case a system reaction is created such assending a message that the celebrity was seen on a certain locationusing twitter.com of Facebook.com.

Abducted children DB in which case a message will be sent to localpolice

A person category DB of police or soldier uniforms.

FIG. 9 is a scheme describing a system and process in accordance with anexemplary embodiment of the invention.

Person 140 drives his vehicle 110.

He is driving towards a pedestrian 902 who is crossing the road. Person

140 is falling asleep or not paying attention to the road.

As a result he doesn't notice pedestrian 902 crossing the road. System490 processes images taken by camera 122 and estimates distance fromand/or the relative speed to pedestrian 902 and the estimated risk foran accident. If such a risk crosses a predefined threshold systemreaction will occur.

FIG. 10 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention.

Scheme shows a vehicle 110 having device 120 and traveling along a road

620. Driver 140 is driving his vehicle 110 and is seeking for a parkingspot.

System 490 processes images of the environment surrounding vehicle 110,

and produces information out of them.

From this information system 490 identifies available parking spots andalerts driver 140 when one is detected 1002. For example pavement stonesmarking an allowed parking place such as 1008 with that are not taken bycars such as 1006 and 1004 and with a length that is above a predefinedlength.

These alerts are also accessible to all system's 490 users withinsuitable range via web.

Driver 140 then reaches parking spot 1002, between two parking vehicles1004, 1006 and tries to park his vehicle 110.

System 490 processes images taken by cameras 122,128 and accordinglycalculates parking route 1012, then system 490 reaction will occur inorder to guide driver 140 into parking spot 1002.

FIG. 11 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention.

Scheme shows a vehicle 110 traveling along a road 620. System 490processes images of the environment in front of the vehicle 110 andrecognizes whether it's a day or a night driving. In case of nightdriving system 490 checks whether vehicle lights 1102 are turned on. Iflights 1102 are off, system 490 preforms a reaction.

Moreover, system 490 recognizes whether vehicle 110 has reached itsdestination 1104 using Micronavigation for example by comparing theinput received by 120 to the known images of taken before on thatcoordinates. In case of destination arrival system produces relevantnotice. Micronavigation can be also used to navigate person 236 to aspecific shelf in store 834. Or to assist a driver in navigation such astelling him to change lanes or take a turn.

FIG. 12 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention.

Information is collected using the act described in FIG. 5 using one ormore systems such as 490 on one or more objects 1210. Optionally foreach object its category 514 and attributes 518 are extracted. Object ofthe same of similar coordinates and or attributes can be counted 1230 inorder to analyze the data. Preparation 1230 is sometimes the preparationsuch as 1240.

The reports of 1240 can be of several categories such as: GISinformation reports, Summarized information and street view includingbusiness names, crowd and traffic.

Examples of such reports are shown in 1260:

A report of vacant parking places: Multiple cars such as 110 are drivingthrough the city as shown in FIG. 13, in case a car comes across avacant parking place, that spot is reported back through a publicnetwork to create the report.

A report of places in the road that require fixing such as 822, that canhelp the municipal authority fix them

A report on businesses on the street, their names and block numbers(using OCR), the amount of traffic that passes next to them such as 832,the number of people inside or waiting outside of them. An the emotionsof these people (using smile recognition and/or analyzing the soundsthat crowd is making)

A report on the overall sentiment in certain city region

A report on the overall status of cars in a certain region such as theirmodels, are they old or new, do they have mechanical problems, what isthe level of pollution they are making.

A report on the status of plants in the city, how many green regions arethree, how many of them need irrigation (using IR), how many of them areblossoming.

A map of the city:

Roads using road recognition (for example many asphalt roads are black)

Buildings, using building recognition.

Street number of each of them using OCR of the street signs

Traffic signs such as 816,824, 600 using content match to traffic signDB, including changing signs such as LED signs

A real time map of the Temperature on different parts of a region, suchas a city temperature map

A report on driver behavior, the data collected by device 120 usingcamera 122 and/or sensors 124, 126 such as: acceleration, speed,accidents, near accidents, collision warnings can all be collected tocreate a database of driver behavior. The specific driver can beidentified using face recognition or by the identity of device 120. Thedata can be used to evaluate the risk of the specific driver making anaccident and an overall risk scoring can be computed for that driver.The result can be the estimated cost of the diver is insurance riskand/or gas consumption to be used by the driver and/or his companyand/or insurer.

A reported on wanted cars, for example each car such as 110, 1310, and

1320 carry system such as 490 using devices such as 120. In case system490 identify a license plate of a neighboring car such as 130, it usesLPR to report the license plate to a remote server such as 1340. Theremote server compares the found license plate to a wanted car databasesuch as stolen cars, fugitives, and people with unpaid debt. In casematch is found a system reaction is created such as an SMS to the localpolice station.

A report of places of interest, for example places where vehicles orpeople tend to slow down or even stop (that could be measured using GPS,acceleration, or the camera) are considered places that create higherlevel of interest.

FIG. 13 is a scheme describing a system and process in accordance withan exemplary embodiment of the invention.

The System is comprised of:

A fleet of platform such as 200, for example cars 110, 1310, 1320 whereeach of them carries devices such as 120. Platforms are connected via apublic network such as wireless Internet 1330 to a remote server 1340.Servers processes the captured by 1302 such as shown in FIG. 5 or step1230. Reports such as 1240,1260 are shown using devices such as 120 oron a remote terminal such as 1342.

FIGS. 14A and 14B are schemes describing a system and process inaccordance with an exemplary embodiment of the invention.

Object A and its coordinates are captured 1450 and its coordinates arerecorder using systems such as a GPS. The same steps are performed onobject B

1452 and data on both objects is stored 1454 in a DB.

Person 236 is moving in direction 1410 and passes by object a marked1422 requests system such as 120 to get to object B or its coordinates.Device 120 uses sensors such as 122, 128, 124, 126 to captureinformation on object 1422 as described in step 1456. The Captured dataon object 1422 is compared against the data in the DB of 1454 to search1458 for a content match. In case content match is found with object Aand using it coordinates navigation instructions are calculated 1460using the coordinates of object B in relation to the coordinates ofobject A and displayed 1462 to person 236.

The system and process can be used for example to navigate in placewhere GPS usage is not possible such as between stores in a shoppingmole, between shelves in a supermarket, and to find ones car in aparking lot for finding the right door in a an office place.

The system can be used for Micronavigation, for example to identify incase someone is navigating in the wrong lane, or took the wrong turn.

FIG. 15 is a schematic illustration of an information display system940, in accordance with an exemplary embodiment of the invention.

System 940 comprises a device 120 with cameras 122,128 which acquiresimages, optionally a video stream of images. The images are provided toa content analysis unit 954 which identifies objects of interest in theimages. Information on the identified objects and optionally theirattributes is forwarded to an information selection unit 958 whichdetermines accordingly what information is to be displayed on a display956, using any of the above described methods.

In an exemplary embodiment of the invention device 120 may monitorpeople, such as person 942, standing near display 956 and selectadvertisements for display 956 according to attributes of the people.For example, advertisements directed to a child audience may bedisplayed when device 954 identifies a large percentage of children inthe images acquired by device 120. Alternatively to being directed at alocation from which display 956 is viewed, camera 952 may view anentrance to a shop or other closed area in which display 956 displaysadvertisements or other information. The advertisements displayed areoptionally selected according to the average profile of people enteringthe shop.

In some embodiments of the invention, the advertisements are selectedresponsive to behavior against rules identified in the images of device120. For example, when a camera monitoring a printer at a work placeidentifies misuse of the printer it may show on display 956 a warningand/or use instructions.

Device 120 is stationary, in some embodiments. In other embodiments ofthe invention, Device 120 is a portable camera, possibly mounted on amobile communication terminal. In these embodiments, display 956 isoptionally the display of the mobile terminal. Alternatively, display956 is separate from the mobile terminal, which periodically transmitsinformation selection instructions to the display. In some embodimentsof the invention, Device 120 stores the selected information until themobile terminal is connected to a base computer. Device 120 may also bemounted on home and/or office appliances, such as refrigerators.

In some embodiments of the invention, the images from device 120 areadditionally provided to a monitoring station 950. Thus, device 120 isused for two different tasks and the cost of camera hardware is reduced.In some embodiments of the invention, installation of system 940 isfinanced by the advertisements.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wire-line, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described above with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other

programmable data processing apparatus, create means for implementingthe functions/acts specified in the flowchart and/or block diagram blockor blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The aforementioned flowchart and diagrams illustrate the architecture,functionality, and operation of possible implementations of systems,methods and computer program products according to various embodimentsof the present invention. In this regard, each block in the flowchart orblock diagrams may represent a module, segment, or portion of code,which comprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block may occurout of the order noted in the figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

In the above description, an embodiment is an example or implementationof the inventions. The various appearances of “one embodiment,” “anembodiment” or “some embodiments” do not necessarily all refer to thesame embodiments.

Although various features of the invention may be described in thecontext of a single embodiment, the features may also be providedseparately or in any suitable combination. Conversely, although theinvention may be described herein in the context of separate embodimentsfor clarity, the invention may also be implemented in a singleembodiment.

Reference in the specification to “some embodiments”, “an embodiment”,“one embodiment” or “other embodiments” means that a particular feature,structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments, of the inventions.

It is to be understood that the phraseology and terminology employedherein is not to be construed as limiting and are for descriptivepurpose only.

The principles and uses of the teachings of the present invention may bebetter understood with reference to the accompanying description,figures and examples.

It is to be understood that the details set forth herein do not construea limitation to an application of the invention.

Furthermore, it is to be understood that the invention can be carriedout or practiced in various ways and that the invention can beimplemented in embodiments other than the ones outlined in thedescription above.

It is to be understood that the terms “including”, “comprising”,“consisting” and grammatical variants thereof do not preclude theaddition of one or more components, features, steps, or integers orgroups thereof and that the terms are to be construed as specifyingcomponents, features, steps or integers.

If the specification or claims refer to “an additional” element, thatdoes not preclude there being more than one of the additional element. \

It is to be understood that where the claims or specification refer to“a” or “an” element, such reference is not be construed that there isonly one of that element.

It is to be understood that where the specification states that acomponent, feature, structure, or characteristic “may”, “might”, “can”or “could” be included, that particular component, feature, structure,or characteristic is not required to be included.

Where applicable, although state diagrams, flow diagrams or both may beused to describe embodiments, the invention is not limited to thosediagrams or to the corresponding descriptions. For example, flow neednot move through each illustrated box or state, or in exactly the sameorder as illustrated and described.

Methods of the present invention may be implemented by performing orcompleting manually, automatically, or a combination thereof, selectedsteps or tasks.

The descriptions, examples, methods and materials presented in theclaims and the specification are not to be construed as limiting butrather as illustrative only.

Meanings of technical and scientific terms used herein are to becommonly understood as by one of ordinary skill in the art to which theinvention belongs, unless otherwise defined.

The present invention may be implemented in the testing or practice withmethods and materials equivalent or similar to those described herein.

Any publications, including patents, patent applications and articles,referenced or mentioned in this specification are herein incorporated intheir entirety into the specification, to the same extent as if eachindividual publication was specifically and individually indicated to beincorporated herein. In addition, citation or identification of anyreference in the description of some embodiments of the invention shallnot be construed as an admission that such reference is available asprior art to the present invention.

While the invention has been described with respect to a limited numberof embodiments, these should not be construed as limitations on thescope of the invention, but rather as exemplifications of some of thepreferred embodiments. Other possible variations, modifications, andapplications are also within the scope of the invention. Accordingly,the scope of the invention should not be limited by what has thus farbeen described, but by the appended claims and their legal equivalents.

What is claimed is:
 1. A system comprising: a server; a plurality ofsmart phone applications which are executed by a plurality of smartphones, each one of said plurality of smart phones having an imagecapturing unit, a positioning unit, and a processing unit, wherein allof the units are physically packed within the smart phone; and whereinwhile said plurality of smart phone applications are executed, each oneof said plurality of smart phones are mounted in a quick mount attachedto a surface within one of a plurality of vehicles; wherein each one ofsaid plurality of smart phones is configured to capture a sequence ofimages and to extract therefrom information about a plurality of surfaceobjects located within a distance from a first vehicle from saidplurality of vehicles; and wherein each one of said plurality of smartapplications instructs the respective processing unit to derive locationdata related to the plurality of surface objects based on positioningmeasurements derived from the positioning unit, wherein each one of saidplurality of smart phone applications is adapted to connect to a remoteserver via a wireless network and to transmit the information and thelocation data of the plurality of surface objects to the server, andwherein the server is adapted to yield a report comprising a map of acity according to an analysis of the information and the location datafrom said plurality of smart phone applications.
 2. The system accordingto claim 1, wherein the processing unit is further configured to apply adecision function to the captured images and to momentary kineticsparameters, to yield an analysis of a risk of a collision between thefirst vehicle and a second vehicle, wherein the smart phone furthercomprises a front camera to capture images of a driver of said firstvehicle, wherein said processing unit is adapted to process said imagesof the driver and to detect, accordingly, physical and cognitiveconditions of the driver, and wherein the processing unit is furtherconfigured to estimate said risk based on said physical and cognitiveconditions.
 3. The system according to claim 1, wherein the processingunit is further configured to apply a decision function to the capturedimages and to momentary kinetics parameters, to yield an analysis of arisk of a collision between the first vehicle and a second vehicle, andwherein the processing unit is adapted to process said sequence ofimages and determine, accordingly, conditions of a road, wherein theprocessing unit is further configured to apply the decision function tothe detected conditions of the road, to yield an improved estimation ofthe risk of collision.
 4. The system according to claim 1, wherein theprocessing unit is further configured to apply a decision function tothe captured images and to momentary kinetics parameters, to yield ananalysis of a risk of a collision between the first vehicle and a secondvehicle, wherein the processing unit is adapted to process said sequenceof images and detect, accordingly, pedestrians, and wherein theprocessing unit is further configured to apply the decision function tothe detected pedestrians to yield an updated estimation of the risk ofcollision.
 5. The system according to claim 1, wherein each one of saidplurality of smart phones is further configured to consume electricityfrom a vehicle mounted power source.
 6. The system according to claim 1,wherein said report maps vacant parking places.
 7. The system accordingto claim 1, wherein said report maps places in a road that arecandidates to be fixed.
 8. The system according to claim 1, wherein saidreport maps businesses on a street.
 9. The system according to claim 1,wherein said report maps overall status of cars in a certain region. 10.The system according to claim 1, wherein said report maps status ofplants in the city.
 11. The system according to claim 1, wherein saidmap of a city maps roads and buildings.
 12. A method comprising:providing at least one smart phone application installed in at least onesmart phone having an image capturing unit, a positioning unit, and aprocessing unit, wherein all of the units are physically packed withinthe smart phone; providing at least one quick mount unit having a firstand a second end, wherein the quick mount unit is shaped to grab the atleast one smart phone on the first end and further configured to attachto a surface within a vehicle of a plurality of vehicles at the secondend; capturing a sequence of images; extracting from said sequence ofimages information about a plurality of surface objects located within adistance from a first vehicle from said plurality of vehicles; derivinglocation data related to the plurality of surface objects based onpositioning measurements derived from the positioning unit in the firstvehicle; connecting to a remote server via a wireless network; andtransmitting the information and the location data of the plurality ofsurface objects to the remote server; wherein the server is adapted toyield a report comprising a map of a city according to an analysis ofthe information and the location data from the at least one smart phoneapplication.
 13. The method according to claim 12, wherein the at leastone quick mount unit comprises a quick release cradle on the first endand a suction cup at the second end.
 14. The method according to claim12, wherein the processing unit is further configured to apply adecision function to the captured images and to momentary kineticsparameters to yield an analysis of a risk of a collision between thefirst vehicle and a second vehicle, wherein the processing unit isadapted to determine physical and cognitive conditions of a driver ofthe first vehicle, and wherein the method further comprises applying thedecision function to the detected driver conditions to yield an updatedestimation of the risk of collision.
 15. The method according to claim12, wherein the processing unit is further configured to apply adecision function to the captured images and to momentary kineticsparameters to yield an analysis of a risk of a collision between thefirst vehicle and a second vehicle, wherein the processing unit isadapted to process said sequence of images and determine, accordingly,conditions of a road, and wherein the method further comprises applyingthe decision function to the determined conditions of the road to yieldan updated estimation of the risk of collision.
 16. The method accordingto claim 12, wherein the processing unit is further configured to applya decision function to the captured images and to momentary kineticsparameters to yield an analysis of a risk of a collision between thefirst vehicle and a second vehicle, wherein the processing unit isadapted to process said sequence of images and detect, accordingly,pedestrians on the captured images, and wherein the method furthercomprises applying the decision function to the detected pedestrians onthe captured images to yield an updated estimation of the risk ofcollision.
 17. The method according to claim 12, wherein the at leastone smart phone is further configured to consume electricity from avehicle-mounted power source.